Hybrid AI–Taguchi–ANOVA for Thermographic Monitoring of Electronic Devices #WorldResearchAwards
Introduction Printed circuit boards (PCBs) are fundamental to modern electronic systems, and their reliability directly affects the performance and safety of critical applications. Undetected defects in PCBs can evolve gradually, leading to unexpected failures and costly downtime. Conventional monitoring techniques, often limited to simulations or surface-level measurements, lack the capability for real-time fault detection and predictive maintenance. This research addresses these limitations by introducing an integrated framework that combines infrared thermography (IRT), artificial intelligence (AI), and Taguchi–ANOVA statistical methods to enable accurate, real-time diagnosis of thermal anomalies in operating PCBs . Infrared Thermography for Real-Time PCB Monitoring Infrared thermography serves as a non-contact, non-destructive technique for capturing thermal signatures of PCBs during normal operation. By visualizing heat distribution and thermal stresses , IRT reveals hi...